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Comments on "Challenges of cellwise outliers" by Jakob Raymaekers and Peter J. Rousseeuw

对《单元格异常值的挑战》的评论

The main aim of robust statistics is the development of methods able to cope with the presence of outliers. A new type of outliers, namely "cellwise", has garnered considerable attention. The state of the art for dealing with cellwise contamination in different models is presented in Raymaekers and Rousseeuw (2024). Outliers in time series can be treated as cellwise outliers, a further discussion on this subject is presented.

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A Robust Seemingly Unrelated Regressions For Row-Wise And Cell-Wise Contamination

同时应对行污染与单元格污染的稳健似不相关回归

The Seemingly Unrelated Regressions (SUR) model is a wide used estimation procedure in econometrics, insurance and finance, where very often, the regression model contains more than one equation. Unknown parameters, regression coefficients and covariances among the errors terms, are estimated using algorithms based on Generalized Least Squares or Maximum Likelihood, and the method, as a whole, is very sensitive to outliers. To overcome this problem M-estimators and…

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